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Assembling and validating data from multiple sources to study care for Veterans with bladder cancer

BACKGROUND: Despite the high prevalence of bladder cancer, research on optimal bladder cancer care is limited. One way to advance observational research on care is to use linked data from multiple sources. Such big data research can provide real-world details of care and outcomes across a large numb...

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Autores principales: Schroeck, Florian R., Sirovich, Brenda, Seigne, John D., Robertson, Douglas J., Goodney, Philip P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585934/
https://www.ncbi.nlm.nih.gov/pubmed/28877694
http://dx.doi.org/10.1186/s12894-017-0271-x
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author Schroeck, Florian R.
Sirovich, Brenda
Seigne, John D.
Robertson, Douglas J.
Goodney, Philip P.
author_facet Schroeck, Florian R.
Sirovich, Brenda
Seigne, John D.
Robertson, Douglas J.
Goodney, Philip P.
author_sort Schroeck, Florian R.
collection PubMed
description BACKGROUND: Despite the high prevalence of bladder cancer, research on optimal bladder cancer care is limited. One way to advance observational research on care is to use linked data from multiple sources. Such big data research can provide real-world details of care and outcomes across a large number of patients. We assembled and validated such data including (1) administrative data from the Department of Veterans Affairs (VA), (2) Medicare claims, (3) data abstracted by tumor registrars, (4) data abstracted via chart review from the national electronic health record, and (5) full text pathology reports. METHODS: Based on these combined data, we used administrative data to identify patients with newly diagnosed bladder cancer who received care in the VA. To validate these data, we first compared the diagnosis date from the administrative data to that from the tumor registry. Second, we measured accuracy of identifying bladder cancer care in VA administrative data, using a random chart review (n = 100) as gold standard. Lastly, we compared the proportion of patients who received bladder cancer care among those who did versus did not have full text bladder pathology reports available, expecting that those with reports are significantly more likely to receive care in VA. RESULTS: Out of 26,675 patients, 11,323 (42%) had tumor registry data available. 90% of these patients had a difference of 90 days or less between the diagnosis dates from administrative and registry data. Among 100 patients selected for chart review, 59 received bladder cancer care in VA, 58 of which were correctly identified using administrative data (sensitivity 98%, specificity 90%). Receipt of bladder cancer care was substantially more common among those who did versus did not have bladder pathology available (96% vs. 43%, p < 0.001). CONCLUSION: Merging administrative with electronic health record and pathology data offers new possibilities to validate the use of administrative data in bladder cancer research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12894-017-0271-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-55859342017-09-06 Assembling and validating data from multiple sources to study care for Veterans with bladder cancer Schroeck, Florian R. Sirovich, Brenda Seigne, John D. Robertson, Douglas J. Goodney, Philip P. BMC Urol Research Article BACKGROUND: Despite the high prevalence of bladder cancer, research on optimal bladder cancer care is limited. One way to advance observational research on care is to use linked data from multiple sources. Such big data research can provide real-world details of care and outcomes across a large number of patients. We assembled and validated such data including (1) administrative data from the Department of Veterans Affairs (VA), (2) Medicare claims, (3) data abstracted by tumor registrars, (4) data abstracted via chart review from the national electronic health record, and (5) full text pathology reports. METHODS: Based on these combined data, we used administrative data to identify patients with newly diagnosed bladder cancer who received care in the VA. To validate these data, we first compared the diagnosis date from the administrative data to that from the tumor registry. Second, we measured accuracy of identifying bladder cancer care in VA administrative data, using a random chart review (n = 100) as gold standard. Lastly, we compared the proportion of patients who received bladder cancer care among those who did versus did not have full text bladder pathology reports available, expecting that those with reports are significantly more likely to receive care in VA. RESULTS: Out of 26,675 patients, 11,323 (42%) had tumor registry data available. 90% of these patients had a difference of 90 days or less between the diagnosis dates from administrative and registry data. Among 100 patients selected for chart review, 59 received bladder cancer care in VA, 58 of which were correctly identified using administrative data (sensitivity 98%, specificity 90%). Receipt of bladder cancer care was substantially more common among those who did versus did not have bladder pathology available (96% vs. 43%, p < 0.001). CONCLUSION: Merging administrative with electronic health record and pathology data offers new possibilities to validate the use of administrative data in bladder cancer research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12894-017-0271-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-09-06 /pmc/articles/PMC5585934/ /pubmed/28877694 http://dx.doi.org/10.1186/s12894-017-0271-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Schroeck, Florian R.
Sirovich, Brenda
Seigne, John D.
Robertson, Douglas J.
Goodney, Philip P.
Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title_full Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title_fullStr Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title_full_unstemmed Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title_short Assembling and validating data from multiple sources to study care for Veterans with bladder cancer
title_sort assembling and validating data from multiple sources to study care for veterans with bladder cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585934/
https://www.ncbi.nlm.nih.gov/pubmed/28877694
http://dx.doi.org/10.1186/s12894-017-0271-x
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